On the icy slopes of expertise: How a Cold War-era solution to the problem of expert opinion in science might transform the epistemology of simulation

This article identifies two major sources of epistemological uncertainty in simulation, the problem of representation-how similar is the model to reality?-and the problem of expert opinions-what status can be ascribed to expert opinions? In the late 1950s, philosophers Olaf Helmer and Nicholas Rescher proposed an epistemology that purportedly provided the foundation for understanding simulation and comparable predictive endeavors as scientific. Published in 1959 as On the Epistemology of the Inexact Sciences, it claimed that under certain provisions, expert opinions should be acknowledged on the same epistemological level as theories or data. Doing so would solve the problem of expert opinion. While this proposal was innovative and soundly argued, it was not much received. Yet, within futures studies, it contributed to the development of an epistemological position, and eventually a new concept of science, that acknowledge and integrate the uncertainty implied in any predictive science. This article argues that it is worthwhile to reconsider Helmer and Rescher's proposal and the ensuing debates about the nature of science in futures studies, as they provide a strategic position from which to re-conceptualize the use of expert opinions in simulation studies and thus to establish a more adequate epistemology for simulation in other fields of science.

Automated summary

This article discusses two sources of epistemological uncertainty in simulation studies: the problem of representation and the problem of expert opinions. It explores the proposal made by Helmer and Rescher in the late 1950s, suggesting that expert opinions should be regarded on the same epistemological level as theories or data. Although their proposal did not receive much attention, it contributed to the development of an epistemological position that acknowledges the uncertainty inherent in predictive sciences. The article argues for reconsidering their proposal to establish a more adequate epistemology for simulation in various fields of science.